Occluded Gesture Recognition

ABSTRACT

This document describes techniques and devices for occluded gesture recognition. Through use of the techniques and devices described herein, users may control their devices even when a user&#39;s gesture is occluded by some material between the user&#39;s hands and the device itself. Thus, the techniques enable users to control their mobile devices in many situations in which control is desired but conventional techniques do permit effective control, such as when a user&#39;s mobile computing device is occluded by being in a purse, bag, pocket, or even in another room.

PRIORITY APPLICATIONS

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 15/703,511 filed Sep. 13, 2017 entitled “OccludedGesture Recognition”, which in turn claims priority to U.S. patentapplication Ser. No. 14/494,863 filed Sep. 24, 2014, now U.S. Pat. No.9,778,749 entitled “Occluded Gesture Recognition”, which in turn claimspriority under 35 U.S.C. § 119(e) to U.S. Provisional Patent ApplicationNo. 62/040,896 filed Aug. 22, 2014 entitled “Occluded GestureRecognition”, the disclosure of which is incorporated in its entirety byreference herein.

BACKGROUND

This background description is provided for the purpose of generallypresenting the context of the disclosure. Unless otherwise indicatedherein, material described in this section is neither expressly norimpliedly admitted to be prior art to the present disclosure or theappended claims.

Mobile computing devices continue to increase in popularity, as thesedevices are small, light, and often have substantial computing andcommunication capabilities. To enjoy these many capabilities, usersdesire seamless and near-constant control of their devices. Conventionaltechniques, however, do not permit seamless and near-constant control.

To address this desire, some other conventional techniques provide audiointerfaces. These audio interfaces can help users control their deviceswhen their hands are occupied and audio interference is minimal, such aswhen driving. These conventional techniques, however, often fail tounderstand a user's commands. Even when these conventional techniques dounderstand a user's commands, they fail to enable control in a large setof circumstances during which control is desired.

SUMMARY

This document describes techniques and devices for occluded gesturerecognition. Through use of the techniques and devices described herein,users may control their devices even when a user's gesture is occludedby some material between the user's hands and the device itself. Thus,the techniques enable users to control their mobile devices in manysituations in which control is desired but conventional techniques dopermit effective control, such as when a user's mobile computing deviceis occluded by being in a purse, bag, pocket, or even in another room.

This summary is provided to introduce simplified concepts relating tooccluded gesture recognition, which is further described below in theDetailed Description. This summary is not intended to identify essentialfeatures of the claimed subject matter, nor is it intended for use indetermining the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of techniques and devices for occluded gesture recognitionare described with reference to the following drawings. The same numbersare used throughout the drawings to reference like features andcomponents:

FIG. 1 illustrates an example environment in which occluded gesturerecognition can be implemented.

FIG. 2 illustrates the mobile computing device of FIG. 1 in greaterdetail.

FIG. 3 illustrates an example 3D volume radar field emitted by theoccluded-gesture recognition system of FIG. 2 as a volumetric cone.

FIG. 4 illustrates an example surface radar field emitted by theoccluded-gesture recognition system of FIG. 2.

FIG. 5 illustrates an example method enabling better recognition of anoccluded gesture by mapping gestures to control inputs for anauthenticated person.

FIG. 6 illustrates an example method enabling occluded gesturerecognition.

FIG. 7 illustrates an example device embodying, or in which techniquesmay be implemented that enable use of, occluded gesture recognition.

DETAILED DESCRIPTION Overview

This document describes techniques and devices enabling occluded gesturerecognition. These techniques and devices enable greater control ofmobile devices through recognizing gestures when those gestures areoccluded from the mobile device.

Consider, for example, a case where a user's smartphone is in her purse.The techniques enable her to control her smartphone without having tofumble through her purse to find her smartphone. Assume that she is in ameeting and her phone begins to ring loudly—rather than have it continueto ring until she finds the smartphone, gets it out of her purse, looksat her touch interface to find a control to mute the volume, and thenselects the mute control—she instead makes a simple gesture “in the air”near her purse and her smartphone is immediately silent.

By way of another example, assume that a user is walking to work on acold, rainy morning. Because of this, his media player is in hisbriefcase, protected from the rain, while he listens with earphonesthrough a personal area network in communication with the media player.Rather than have to hold and interact with the media player, thetechniques enable him to pause, adjust a volume, or advance to anothersong simply with a gesture made “in the air”—he need not touch his mediaplayer or even the earphones in his ears. The techniques even enable theuser to make a gesture while his hands are in his jacket pockets,protected from the cold.

These are but two examples in which occluded gesture recognition can beperformed. This document now turns to an example environment, afterwhich example occluded-gesture recognition systems, example methods, andan example computing system are described.

Example Environment

FIG. 1 is an illustration of an example environment 100 in whichtechniques enabling occluded gesture recognition can be performed.Environment 100 includes a mobile computing device 102 having anoccluded-gesture recognition system 104, a closed purse 106, a person108, a hand 110 of person 108 performing an up-and-down gesture 112, anda radar field 114 generated by occluded-gesture recognition system 104.As shown, mobile computing device 102 is within closed purse 106 andthus hand 110 is occluded from mobile computing device 102 due to thematerial of closed purse 106. Radar field 114, described in detailbelow, is configured to penetrate various materials, such as wool,cotton, nylon, or leather, but reflect from human tissue of hand 110,thereby enabling recognition of occluded gestures.

In more detail, consider FIG. 2, which illustrates mobile computingdevice 102 including one or more computer processors 202 andcomputer-readable media 204, which includes memory media and storagemedia. Applications and/or an operating system (not shown) embodied ascomputer-readable instructions on computer-readable media 204 can beexecuted by processors 202 to provide some of the functionalitiesdescribed herein. Computer-readable media 204 also includes gesturemanager 206 (described below).

Computing device 102 may also include network interfaces 208 forcommunicating data over wired, wireless, or optical networks. By way ofexample and not limitation, network interface 208 may communicate dataover a local-area-network (LAN), a wireless local-area-network (WLAN), apersonal-area-network (PAN), a wide-area-network (WAN), an intranet, theInternet, a peer-to-peer network, point-to-point network, a meshnetwork, and the like. Mobile computing device 102 may also include adisplay 210, though this is not required.

Occluded-gesture recognition system 104, as noted above, is configuredto sense gestures. To enable this, occluded-gesture recognition system104 includes a microwave radio element 212, an antenna element 214, anda signal processor 216. Generally, microwave radio element 212 isconfigured to provide a radar field that is capable of penetrating somematerials, such as textiles, and reflecting from other materials, suchas human tissue. While examples shown herein generally show oneoccluded-gesture recognition system 104 per device, multiples can beused, thereby increasing a number and complexity of gestures, as well asaccuracy, resolution, and robust recognition.

This radar field can be large or small and be widely dispersed ornarrowly directed (e.g., focused). In some cases described below, theradar field is directed to a particular user's hands, which can improveaccuracy, reduce power costs, and/or direct reception of gestures tothose of an identified hand.

Microwave radio element 212 can be configured to emit continuouslymodulated radiation, ultra-wideband radiation, orsub-millimeter-frequency radiation. Microwave radio element 212, in somecases, is configured to form radiation in beams, the beams aidingantenna element 214 and signal processor 216 to determine which of thebeams are interrupted, and thus locations of interactions (e.g., by ahand) within the radar field. In more detail, microwave radio element212 can be configured to emit microwave radiation in a 1 GHz to 300 GHzrange, as well as 57 GHz to 63 GHz, to provide the radar field. Thisrange affects antenna element 214's ability to sense interactions, suchas to track locations of two or more targets to a resolution of abouttwo to about 25 millimeters. Microwave radio element 212 can beconfigured, along with other entities of occluded-gesture recognitionsystem 104, to have a relatively fast update rate, which can aid inresolution of the interactions. By selecting particular frequencies,occluded-gesture recognition system 104 can operate to substantiallypenetrate clothing while not substantially penetrating human tissue.

Antenna element 214 is configured to receive reflections of, or senseinteractions in, the radar field, and signal processor 216 is configuredto process the reflections or sensed interactions in the radar fieldsufficient to provide gesture data usable to determine a gesture fromthe sensed interactions. Antenna element 214 can include one or manysensors, such as an array of radiation sensors, the number in the arraybased on a desired resolution and whether the field is a surface, plane,or volume. Alternately or additionally, antenna element 214 may includeone or many antennas, such as an array of antennas, directional orotherwise, coupled with respective radiation sensors and/or signalprocessor 216.

Further, antenna element 214 or signal processor 216 can be configuredto differentiate between interactions in the radar field caused byclothing from those interactions in the radar field caused by humantissue. Thus, a user with a smartphone 102-1 (that includesoccluded-gesture recognition system 104) that is placed within a jacketor shirt pocket covering microwave radio element 212, and even withhands wearing gloves or in another pocket may still control the mobilecomputing device 102 through use of occluded-gesture recognition system104.

The field provided by microwave radio element 212 can be athree-dimensional (3D) volume (e.g., hemisphere, cube, cylinder, cone),a plane, or a surface applied to human tissue or non-human object. Inthe case of a 3D volume, antenna element 214 is configured to senseinteractions in the 3D volume of multiple targets (e.g., two hands,fingers of one or two hands, etc.), and signal processor 216 isconfigured to process the sensed interactions in the 3D volumesufficient to provide gesture data usable to determine gestures in threedimensions.

An example of a 3D volume is illustrated in FIG. 3, which shows a 3Dvolume radar field 302, formed as two volumetric cones 304 and emittedby occluded-gesture recognition system 104 of media player 306. Notethat media player 306 is placed within, and occluded by, fabric of man308's jacket 310. As described later below, 3D volume radar field 302can be directed toward particular locations, such as through tracking ofman 308's hands 312.

With 3D volume radar field 302, a user may perform complex or simplegestures with a hand or device (e.g., a stylus) that interrupts thevolume. Example gestures include the many gestures usable with currenttouch-sensitive displays, such as swipes, two-finger pinch and spread,tap, and so forth. Other gestures are enabled that are complex, orsimple but three-dimensional, examples include the many sign-languagegestures, e.g., those of American Sign Language (ASL) and other signlanguages worldwide. A few of these include an up-and-down fist, whichin ASL means “Yes”, an open index and middle finger moving to connect toan open thumb, which means “No”, a flat hand moving up a step, whichmeans “Advance”, a flat and angled hand moving up and down, which means“Afternoon”, clenched fingers and open thumb moving to open fingers andan open thumb, which means “taxicab”, an index finger moving up in aroughly vertical direction, which means “up”, and so forth. These arebut a few of many gestures that can be mapped to particular devices orapplications, such as the “Advance” gesture to skip to another songbeing played by media player 306 through an occluded gesture performedby man 308's hand 312.

The radar field can also include a surface applied to human tissue. Thisis illustrated at FIG. 4, which shows hand 402 having a surface radarfield 404 provided by occluded-gesture recognition system 104 of laptop102-7. Radio emitter 212 (not shown) provides surface radar field 404penetrating chair 406 and applied to hand 402. In this case, antennaelement 214 (not shown) is configured to receive a reflection caused byan interaction on the surface of hand 402 that penetrates (e.g.,reflects back through) chair 406 and signal processor 216 is configuredto process the received reflection on the surface sufficient to providegesture data usable to determine a gesture. Note that with surface radarfield 404, another hand may interact to perform gestures, such as to tapon the surface on hand 402, thereby interacting with surface radar field404. Example gestures include single and multi-finger swipe, spread,squeeze, non-linear movements, and so forth. Or hand 402 may simply moveor change shape to cause reflections, thereby also performing anoccluded gesture.

Gestures can be mapped to various control inputs, thereby enablingcontrol of many devices and applications. Many complex and uniquegestures can be recognized by occluded-gesture recognition systems 104,thereby permitting precise and/or single-gesture control, even formultiple applications. Occluded-gesture recognition systems 104, whileshown integral with mobile computing device 102, can be instead be partof a device having few or no computing capabilities, instead providinggesture data to be recognized and/or mapped to a control input.Occluded-gesture recognition system 104 can communicate with otherdevices through network interface 208 through a network, such as one ormore of many types of wireless or partly wireless communicationnetworks, such as a local-area-network (LAN), a wirelesslocal-area-network (WLAN), a personal-area-network (PAN), awide-area-network (WAN), an intranet, the Internet, a peer-to-peernetwork, point-to-point network, a mesh network, and so forth.

Mobile computing device 102 is illustrated with various non-limitingexample devices: smartphone 102-1, computing spectacles 102-2, camera102-3, tablet 102-4, computing bracelet 102-5, computing ring 102-6, andlaptop 102-7, though other devices may also be used, such as wearabledevices such as a brooch or necklace, netbooks, and e-readers.

Occluded-gesture recognition system 104 also includes a transceiver 218configured to transmit gesture data to a remote device, such as in caseswhere occluded-gesture recognition system 104 is not integrated withmobile computing device 102. Gesture data can be provided in a formatusable by the receiving device sufficient to recognize a gesture usingthe gesture data.

Occluded-gesture recognition system 104 may also include one or moresystem processors 220 and system media 222 (e.g., one or morecomputer-readable storage media). System media 222 includes systemmanager 224, which can perform various operations, including determininga gesture based on gesture data from signal processor 216, mapping thedetermined gesture to a pre-configured control gesture associated with acontrol input for an application associated with remote device, andcausing transceiver 218 to transmit the control input to the remotedevice effective to enable control of the application or device. This isbut one of the ways in which the above-mentioned control throughoccluded-gesture recognition system 104 can be enabled. Operations ofsystem manager 224 are provided in greater detail as part of methods 5and 6 below.

These and other capabilities and configurations, as well as ways inwhich entities of FIGS. 1-4 act and interact, are set forth in greaterdetail below. These entities may be further divided, combined, and soon. The environment 100 of FIG. 1 and the detailed illustrations ofFIGS. 2-4 illustrate some of many possible environments and devicescapable of employing the described techniques.

Example Methods

FIGS. 5 and 6 depict methods 500 and 600. Method 500 can be performed tobetter enable later recognition of an occluded gesture by mappinggestures to control inputs for an authenticated person. Method 600enables occluded gesture recognition, and can be performed separate fromor integrated in whole or in part with method 500. These methods andother methods herein are shown as sets of operations (or acts) performedbut are not necessarily limited to the order or combinations in whichthe operations are shown herein. Further, any of one or more of theoperations may be repeated, combined, reorganized, or linked to providea wide array of additional and/or alternate methods. In portions of thefollowing discussion reference may be made to environment 100 of FIG. 1and entities detailed in FIGS. 2-4, reference to which is made forexample only. The techniques are not limited to performance by oneentity or multiple entities operating on one device.

At 502 a person permitted to control a mobile computing device isauthenticated. This authentication can be performed in various mannersknown in the art of authenticating persons generally, such as receivingauthentication credentials and confirming that these credentials matchthe person.

In some cases, however, authenticating the person permitted to controlthe mobile computing device authenticates a person based on identifyingindicia. For example, gesture manager 206 may provide a radar field,receive a human-tissue reflection, determine identifying indicia basedon the human-tissue reflection, and confirm that the identifying indiciamatches recorded identifying indicia for the person permitted to controlthe mobile computing device. These identifying indicia can includevarious biometric identifiers, such as a size, shape, ratio of sizes,cartilage structure, and bone structure for the person or a portion ofthe person, such as the person's hand. These identify indicia may alsobe associated with a device worn by the person permitted to control themobile computing device, such as device having a unique ordifficult-to-copy reflection (e.g., a wedding ring of 14 carat gold andthree diamonds, which reflects radar in a particular manner).

At 504, identifying indicia for a hand of the authenticated person isdetermined. This identifying indicia can be the indicia used forauthentication at operation 502, though that is not required. Thus, insome cases the identifying indicia for the hand of the authenticatedperson includes providing a radar field, receiving multiple human-tissuereflections caused by the hand within the radar field, and determiningthe identifying indicia for the hand based on the multiple human-tissuereflections.

At 506, a hand gesture of the authenticated person's hand is received.In some cases the hand gesture is received responsive to presenting aproposed gesture and a proposed control input to cause with the proposedgesture. Thus, gesture manager 206 may present a gesture and itscorresponding control input, such as in text: “make a flicking gesture”or showing an animation or video of the gesture, and then receive thegesture made by the authenticated person. This hand gesture can then berecorded as an aid in improved recognition, as the manner in which thegesture is made can vary from person to person. To do so, gesturemanager 206 may provide a radar field, receive human-tissue reflectionscaused by the hand gesture within the radar field, and recordgesture-specific indicia for the hand gesture based on the human-tissuereflections. These gestures may also be responsive to presentation ofone or more control inputs and then receiving a gesture that is desiredfor use as that control. This permits users to decide the gesture thatthey want to use, such as a two-finger flick to advance media or pagesof a document, a slashing movement to mute volume, or the various ASLgestures as noted above.

At 508, the received hand gesture is mapped to a control input. This canbe the control input already associated with a presented gesture, or anew gesture selected to be mapped to a control input, and so forth. Thismapping can be as simple as a look-up table, for example, whetherpersonalized and custom or otherwise.

At 510, the identifying indicia and the mapping of the received handgesture are recorded. This recordation is effective to enable alater-received hand gesture to be authenticated as from the personpermitted to control the mobile computing device and mapped to thecontrol input.

Method 600 enables occluded gesture recognition, thereby enablingrecognition of gestures where the gesture actor (e.g., a hand, arm, orstylus) is occluded from a mobile computing device.

At 602, a radar field is provided through one or more occlusions, suchas in the various manners noted above. Gesture manager 206 and/or systemmanager 224 directs the radar field to a user's hand, hands, or othergesture-making device or appendage. In one such case, the techniquesprovide the radar field direct to a region in which gestures areanticipated. This direction can be determined based on a location and/ororientation of the mobile computing device relative to a location of aperson known to be associated with the mobile computing device. Thus, amobile computing device within a front pocket of a person's shirt on theright side can determine this location and, based on it, determine alikely location of the user's hands. In such a case, the mobilecomputing device may also determine an orientation of the devicerelative to the person, such as through the use of accelerometers,acoustic sensors, thermal sensors, light sensors (e.g., front/rearfacing cameras), and the like.

In another case, gesture manager 206 and/or system manager 224 tracksthe particular person's hands after authentication by methods 500. Thus,the person is authenticated at a particular time and a position orlocation of his or her hands are tracked from that time until some lateroperation of method 600. By so doing, the hands' locations are known,which aids in responsive recognition as well as ensuring that control ispermitted by a person having the right to control the mobile device.

Directing the radar field can also save power, as the radar field can besmaller than a more-general radar field occupying a larger volume. Thelocation of the person's hand, for example, can be determined responsiveto identifying the hand based on identifying indicia of the hand asdescribed above. Occluded-gesture recognition system 104 may then trackthe hand to provide a directed radar field. In cases where the person isauthenticated without using identifying indicia (e.g., by entry of apassword), the identifying indicia can simply be a reliable manner oftracking the person's hand or hands, which may involve biometrics, orsufficient information about the hand to continue to track the hand,which is not necessarily information sufficient to authenticate it.

At 604, an interaction of an occluded gesture is sensed within the radarfield. This interaction includes the many noted above, such as aup-and-down first to represent a “Yes” selection, a two-finger tapgesture, or a two-handed gesture, such as tapping opposing index,middle, and thumbs against each other through a plane or volume torepresent an “eat” entry, as is the meaning in some sign languages. Thesensed interaction can be processed by signal processor 216, which mayprovide gesture data for later determination as to the gesture intended,such as by system manager 224 or gesture manager 206 as noted herein.

Following 604, method 600 may proceed to operations 606 and 608, thoughthis is optional. At 606, an identity of a person making the occludedgesture is determined. This determination can be made based onidentifying indicia as described in detail above for the hand orappendage or after determining the identity of the person and that theperson's hand is making the gesture. This identifying can be immediateor part of a prior credential authentication and then an ongoingtracking of the person or a hand that performs the occluded gesture. At608, method 600 proceeds along “No” path to operation 602 if the personis not identified as being permitted to control the mobile computingdevice or along the “Yes” path to operation 610 if the person isidentified as permitted to control the mobile computing device.

At 610, the occluded gesture is recognized, such as in the variousmariners described above. This occluded gesture can be recognizedthrough one or more occlusions, such as wool for a wool jacket, denimfor jeans, cotton for a blouse or shirt, or more-substantial occlusions,such as glass or wood furniture, covering and framing of a couch, orfiber-board wall in a home or apartment.

At 612, a control input associated with the recognized gesture isdetermined. Determining the control input associated with the recognizedgesture can be based on a mapping of the recognized gesture to a controlinput or multiple control inputs previously associated with gestures. Ifthere is more than one control input mapped to the recognized gesture,gesture manager 206 can determine which control input to associate therecognized gesture with based on other factors. These other factors mayinclude control inputs associated with a currently executing program, adevice having recently received a control input from the person, amost-common application or device for the user to control, various otherhistoric data, and so forth.

At 614, the determined control input is passed to an entity effective tocontrol the entity. As noted, this entity can be an operating system orapplication associated with mobile computing device 102, though it mayalso be passed to a remote device directly from occluded-gesturerecognition system 104 or through mobile computing device 102.

Thus, a user may make a gesture to pause playback of media on a remotedevice and, at 614, the gesture is passed to the remote device effectiveto pause the playback. In some embodiments, therefore, occluded-gesturerecognition system 104 and these techniques enable implementation of auniversal controller for televisions, media devices, computers,appliances, and so forth.

In cases where operations 606 and 608 are performed, passing the controlinput or some prior operations is responsive to determining that theidentified person is permitted to control the mobile computing device.By so doing control is not permitted by some other person, whether byaccident or for malicious intent.

The preceding discussion describes methods relating to occluded gesturerecognition. Aspects of these methods may be implemented in hardware(e.g., fixed logic circuitry), firmware, software, manual processing, orany combination thereof. These techniques may be embodied on one or moreof the entities shown in FIGS. 1-4 and 7 (computing system 700 isdescribed in FIG. 7 below), which may be further divided, combined, andso on. Thus, these figures illustrate some of the many possible systemsor apparatuses capable of employing the described techniques. Theentities of these figures generally represent software, firmware,hardware, whole devices or networks, or a combination thereof.

Example Computing System

FIG. 7 illustrates various components of example computing system 700that can be implemented as any type of client, server, and/or computingdevice as described with reference to the previous FIGS. 1-6 toimplement an occluded gesture recognition. In embodiments, computingsystem 700 can be implemented as one or a combination of a wired and/orwireless wearable device, System-on-Chip (SoC), and/or as another typeof device or portion thereof. Computing system 700 may also beassociated with a user (e.g., a person) and/or an entity that operatesthe device such that a device describes logical devices that includeusers, software, firmware, and/or a combination of devices.

Computing system 700 includes communication devices 702 that enablewired and/or wireless communication of device data 704 (e.g., receiveddata, data that is being received, data scheduled for broadcast, datapackets of the data, etc.). Device data 704 or other device content caninclude configuration settings of the device, media content stored onthe device, and/or information associated with a user of the device.Media content stored on computing system 700 can include any type ofaudio, video, and/or image data. Computing system 700 includes one ormore data inputs 706 via which any type of data, media content, and/orinputs can be received, such as human utterances, interactions with aradar field, user-selectable inputs (explicit or implicit), messages,music, television media content, recorded video content, and any othertype of audio, video, and/or image data received from any content and/ordata source.

Computing system 700 also includes communication interfaces 708, whichcan be implemented as any one or more of a serial and/or parallelinterface, a wireless interface, any type of network interface, a modem,and as any other type of communication interface. Communicationinterfaces 708 provide a connection and/or communication links betweencomputing system 700 and a communication network by which otherelectronic, computing, and communication devices communicate data withcomputing system 700.

Computing system 700 includes one or more processors 710 (e.g., any ofmicroprocessors, controllers, and the like), which process variouscomputer-executable instructions to control the operation of computingsystem 700 and to enable techniques for, or in which can be embodied,occluded gesture recognition. Alternatively or in addition, computingsystem 700 can be implemented with any one or combination of hardware,firmware, or fixed logic circuitry that is implemented in connectionwith processing and control circuits which are generally identified at712. Although not shown, computing system 700 can include a system busor data transfer system that couples the various components within thedevice. A system bus can include any one or combination of different busstructures, such as a memory bus or memory controller, a peripheral bus,a universal serial bus, and/or a processor or local bus that utilizesany of a variety of bus architectures.

Computing system 700 also includes computer-readable media 714, such asone or more memory devices that enable persistent and/or non-transitorydata storage (i.e., in contrast to mere signal transmission), examplesof which include random access memory (RAM), non-volatile memory (e.g.,any one or more of a read-only memory (ROM), flash memory, EPROM,EEPROM, etc.), and a disk storage device. A disk storage device may beimplemented as any type of magnetic or optical storage device, such as ahard disk drive, a recordable and/or rewriteable compact disc (CD), anytype of a digital versatile disc (DVD), and the like. Computing system700 can also include a mass storage media device 716.

Computer-readable media 714 provides data storage mechanisms to storedevice data 704, as well as various device applications 718 and anyother types of information and/or data related to operational aspects ofcomputing system 700. For example, an operating system 720 can bemaintained as a computer application with computer-readable media 714and executed on processors 710. Device applications 718 may include adevice manager, such as any form of a control application, softwareapplication, signal-processing and control module, code that is nativeto a particular device, a hardware abstraction layer for a particulardevice, and so on.

Device applications 718 also include any system components, engines, ormanagers to implement occluded gesture recognition. In this example,device applications 718 include gesture manager 206 and system manager224.

CONCLUSION

Although embodiments of techniques using, and apparatuses enabling,occluded gesture recognition have been described in language specific tofeatures and/or methods, it is to be understood that the subject of theappended claims is not necessarily limited to the specific features ormethods described. Rather, the specific features and methods aredisclosed as example implementations enabling occluded gesturerecognition.

What is claimed is:
 1. A method performed by a smartphone, the method comprising: determining that the smartphone is in a location corresponding to a pocket of a user based on sensor data provided by at least one sensor; providing a radar field emanating through an occlusion from inside the pocket to outside the pocket, the radar field encompassing a likely location where a gesture is to be made with the user's hand; producing an audible sound; receiving, through the occlusion, a human-tissue reflection of the gesture performed by the user's hand; recognizing, based on the human-tissue reflection, that the gesture is associated with a control input to mute the smartphone; and muting the audible sound responsive to recognizing the gesture.
 2. The method of claim 1, wherein the at least one sensor comprises at least one of the following: an accelerometer; an acoustic sensor; a thermal sensor; a light sensor; or a camera.
 3. The method of claim 1, wherein: the determining that the smartphone is in the pocket comprises determining that the smartphone is in a pocket of the user's purse.
 4. The method of claim 1, wherein: the providing of the radar field comprises directing the radar field to encompass the likely location based on the location of the smartphone in the pocket.
 5. The method of claim 4, further comprising: determining an orientation of the smartphone, wherein: the directing of the radar field is based on both the location of the smartphone and the orientation of the smartphone in the pocket.
 6. The method of claim 1, further comprising: prior to producing the audible sound, tracking the user's hand using the radar field.
 7. The method of claim 6, further comprising: adjusting a volume of the radar field based on the tracking of the user's hand to conserve power.
 8. The method of claim 6, further comprising: authenticating the user based on authentication credentials; initiating the tracking of the user's hand responsive to authenticating the user; and identifying the user based on the tracking of the user's hand.
 9. A smartphone comprising: a speaker configured to produce an audible sound; at least one sensor configured to produce sensor data; an occluded-gesture recognition system configured to: determine that the smartphone is in a pocket of a user based on the sensor data provided by the at least one sensor; provide a radar field emanating through an occlusion from inside the pocket to outside the pocket, the radar field encompassing a likely location where a gesture is to be made with the user's hand; receive, through the occlusion, a human-tissue reflection of the gesture performed by the user's hand after the speaker produces the audible sound; and recognize, based on the human-tissue reflection, that the gesture is associated with a control input to mute the smartphone; and a gesture manager configured to: mute the audible sound responsive to accepting the control input from the occluded-gesture recognition system.
 10. The smartphone of claim 9, wherein the at least one sensor comprises at least one of the following: an accelerometer; an acoustic sensor; a thermal sensor; a light sensor; or a camera.
 11. The smartphone of claim 9, wherein: the occluded-gesture recognition system is further configured to determine that the pocket comprises a pocket on a right side of the user.
 12. The smartphone of claim 9, wherein the occluded-gesture recognition system is configured to: determine an orientation of the smartphone based on the sensor data; and direct the radar field to encompass the likely location based on both a location of the smartphone corresponding to the pocket and the orientation of the smartphone within the pocket.
 13. The smartphone of claim 9, wherein: the occluded-gesture recognition system is configured to track the user's hand using the radar field prior to the speaker producing the audible sound.
 14. The smartphone of claim 13, wherein: the occluded-gesture recognition system is configured to adjust a volume of the radar field based on the tracking of the user's hand.
 15. The smartphone of claim 13, wherein: the occluded-gesture recognition system is further configured to initiate tracking of the user's hand responsive to the smartphone authenticating the user; and the gesture manager is configured to identify the user based on the tracking of the user's hand.
 16. A smartphone comprising: a speaker configured to produce an audible sound; at least one sensor configured to produce sensor data; an occluded-gesture recognition system configured to: receive, through an occlusion, a human-tissue reflection of a gesture performed by a user's hand after the speaker produces the audible sound, the human-tissue reflection occurring at a likely location where a gesture is to be made with the user's hand; one or more computer processors; and one or more computer-readable storage media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising: determining that the smartphone is in a pocket of the user based on the sensor data; recognizing, based on the human-tissue reflection, that the gesture is associated with a control input to mute the smartphone; and muting the audible sound responsive to recognizing the gesture.
 17. The smartphone of claim 16, wherein the at least one sensor comprises an accelerometer.
 18. The smartphone of claim 16, wherein: the operation of determining that the smartphone is in the pocket further comprises determining an orientation of the smartphone within the pocket based on the sensor data; and the occluded-gesture recognition system is configured to determine the likely location where the gesture is to be made based on both a location of the smartphone corresponding to the pocket and the orientation of the smartphone within the pocket.
 19. The smartphone of claim 16, wherein: the operation of determining that the smartphone is in the pocket further comprises determining that the pocket corresponds to a front pocket on the user's clothing.
 20. The smartphone of claim 16, wherein: the occluded-gesture recognition system is configured to track the user's hand to determine the likely location where the gesture is to be made with the user's hand. 